Current status of screening and management of gestational diabetes in early pregnancy: a questionnaire survey in Japan.
Maki YokoyamaKei MiyakoshiSayuri NakanishiNoriyuki IwamaShigeru AokiIchiro YasuhiTakashi SugiyamaPublished in: Diabetology international (2024)
Our aim is to investigate the obstetric practices in Japan regarding the screening and management of gestational diabetes mellitus (GDM) diagnosed before 20 weeks of gestation (early-GDM). A web-based questionnaire survey was administered to 991 teaching hospitals between November 2021 and February 2022, and 602 responses were received (a response rate of 61%). Screening tests for all pregnant women in the first trimester were conducted in 553 (92%) hospitals, and nearly all of these hospitals (535/553 [97%]) adhered to an individual protocol, predominantly relying on random plasma glucose measurements (488/535 [91%]). A quarter (139 [26%]) implemented a risk profile assessment for GDM screening, taking into account factors such as previous gestational diabetes, prior macrosomia, and family history of diabetes. A small number (23 [4%]) targeted only women at high risk of GDM using the risk profile assessment. The majority of hospitals (501 [94%]) employed a 75 g oral glucose tolerance test as a diagnostic measure, and glycemic control for early-GDM was established in most hospitals (429 [80%]). Of the 535 hospitals that maintained an individual management protocol, 356 [67%] facilitated dietary management, self-monitoring of blood glucose, and insulin administration if needed to meet glycemic targets. Our survey revealed a widespread adoption of universal screening and subsequent treatment for early-GDM in Japan.
Keyphrases
- glycemic control
- blood glucose
- type diabetes
- pregnant women
- healthcare
- cross sectional
- pregnancy outcomes
- randomized controlled trial
- current status
- cardiovascular disease
- weight loss
- primary care
- preterm infants
- medical students
- polycystic ovary syndrome
- skeletal muscle
- psychometric properties
- drug delivery
- single cell
- cancer therapy
- neural network
- clinical evaluation